dt1rbfgjdtdsyjynet.m

对动态一阶对象采用RBF神经网络进行建模的源程序,经过调试,直接就可以由MATLAB运行!

function main()
clear all;
close all;

K=1;
T=240;
Ts=20;
num=K;
den=[T,1];
G=tf(num,den,'inputdelay',320)
Gd=c2d(G,Ts,'zoh')
[numd,dend]=c2dm(num,den,Ts)

alldatanum=600;
traindatanum=300;
testdatanum=300;
sp=6.4;
errorlimit=0.00000001;

u=[rands(1,traindatanum) ones(1,testdatanum+20)];
y=zeros(1,alldatanum+20);
for i=18:alldatanum+19
    y(i)=-dend(2)*y(i-1)+numd(2)*u(i-17);
end

alldatain=[];
alldataout=[];
for i=18:alldatanum+19
    newin=[u(i-17);y(i-1)];
    alldatain=[alldatain newin];
    alldataout=[alldataout y(i)];
end

traindatain=alldatain(:,1:traindatanum);
traindataout=alldataout(:,1:traindatanum);
testdatain=alldatain(:,traindatanum+1:alldatanum);
testdataout=alldataout(:,traindatanum+1:alldatanum);

figure
hold on
grid
j=traindatanum+1:alldatanum
plot(j,testdatain,'k-')
xlabel('input t');
ylabel('output u');

figure
hold on
grid
j=traindatanum+1:alldatanum
plot(j,testdataout,'b-')
xlabel('input t');
ylabel('output y');

[indim,maxunitnum]=size(traindatain);

distance=dist(traindatain',traindatain);
hiddenunitout=radbas(distance/sp);

posselected=[];
vectorsselected=[];
hiddenunitoutselected=[];
errorhistory=[];

vectorsselectfrom=hiddenunitout;

dd=sum((traindataout.*traindataout)')';
for k=1:maxunitnum
    pp=sum(vectorsselectfrom.*vectorsselectfrom)';
    denominator=dd*pp';
    [xxx,selectednum]=size(posselected);
    if selectednum>0,
        [lin,xxx]=size(denominator);
        denominator(:,posselected)=ones(lin,1);
    end
    angle=((traindataout*vectorsselectfrom).^2)./denominator;
    
    [value,pos]=max(angle);
    posselected=[posselected pos];
    
    hiddenunitoutselected=[hiddenunitoutselected;hiddenunitout(pos,:)];
    hiddenunitoutex=[hiddenunitoutselected;ones(1,traindatanum)];
    w2ex=traindataout*pinv(hiddenunitoutex);
    w2=w2ex(:,1:k);
    b2=w2ex(:,k+1);
    nnout=w2*hiddenunitoutselected+b2;
    SSE=sumsqr(traindataout-nnout)
    
    errorhistory=[errorhistory SSE];
    
    if SSE<errorlimit,break,end
    
   newvector=vectorsselectfrom(:,pos);
   projectionlen=newvector'*vectorsselectfrom/(newvector'*newvector);
   vectorsselectfrom=vectorsselectfrom-newvector*projectionlen;
end

unitcenters=traindatain(:,posselected);

testdistance=dist(unitcenters',testdatain);
testhiddenunitout=radbas(testdistance/sp);
testnnout=w2*testhiddenunitout+b2;
plot(j,testnnout,'r-')

k
unitcenters
w2
b2

figure
hold on
grid
[xx,num]=size(errorhistory);
plot(1:num,errorhistory,'r-');